U.S. patent number 8,694,176 [Application Number 13/072,886] was granted by the patent office on 2014-04-08 for power control method, and power control apparatus.
This patent grant is currently assigned to Fujitsu Limited. The grantee listed for this patent is Nobutsugu Fujino, Tadanobu Tsunoda, Kazumasa Ushiki, Hiroshi Yamamoto. Invention is credited to Nobutsugu Fujino, Tadanobu Tsunoda, Kazumasa Ushiki, Hiroshi Yamamoto.
United States Patent |
8,694,176 |
Yamamoto , et al. |
April 8, 2014 |
Power control method, and power control apparatus
Abstract
A power control method for a power supplying unit for supplying
power from a commercial power supply and a battery to a load. The
method includes (a) calculating a deviation amount between an
actual power demand and a predicted power demand in a predetermined
unit period on the basis of power demand transition data and power
demand prediction data, (b) correcting, by a computer, a leveling
target value on the basis of the calculated deviation amount, and
(c) controlling the power supplying unit so that the power
supplying unit supplies power corresponding to the corrected
leveling target value from the commercial power supply. The power
demand transition data is stored in a power database, and the power
demand prediction data is stored in a prediction data storing unit.
The leveling target value is a target value of power to be supplied
from the commercial power supply.
Inventors: |
Yamamoto; Hiroshi (Nagaoka,
JP), Ushiki; Kazumasa (Kawasaki, JP),
Tsunoda; Tadanobu (Kawasaki, JP), Fujino;
Nobutsugu (Kawasaki, JP) |
Applicant: |
Name |
City |
State |
Country |
Type |
Yamamoto; Hiroshi
Ushiki; Kazumasa
Tsunoda; Tadanobu
Fujino; Nobutsugu |
Nagaoka
Kawasaki
Kawasaki
Kawasaki |
N/A
N/A
N/A
N/A |
JP
JP
JP
JP |
|
|
Assignee: |
Fujitsu Limited (Kawasaki,
JP)
|
Family
ID: |
44788819 |
Appl.
No.: |
13/072,886 |
Filed: |
March 28, 2011 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20110257803 A1 |
Oct 20, 2011 |
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Foreign Application Priority Data
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Apr 16, 2010 [JP] |
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2010-095154 |
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Current U.S.
Class: |
700/297; 700/286;
700/291; 700/295 |
Current CPC
Class: |
G06F
1/28 (20130101); G06F 1/263 (20130101); G06F
1/305 (20130101) |
Current International
Class: |
G05D
3/12 (20060101); G05D 5/00 (20060101); G05D
9/00 (20060101); G05D 11/00 (20060101); G05D
17/00 (20060101) |
Field of
Search: |
;700/286,291,295,297 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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08-287958 |
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Nov 1996 |
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JP |
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2001-008385 |
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Jan 2001 |
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JP |
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2003-244840 |
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Aug 2003 |
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JP |
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2005-218193 |
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Aug 2005 |
|
JP |
|
Primary Examiner: Hartman, Jr.; Ronald D.
Attorney, Agent or Firm: Fujitsu Patent Center
Claims
What is claimed is:
1. A power control method for a power supplying unit for supplying
power from a commercial power supply and a battery to a load,
comprising: calculating a deviation amount between an actual power
demand and a predicted power demand in a predetermined unit period
on the basis of power demand transition data and power demand
prediction data, the power demand transition data being stored in a
power database, the power demand prediction data being stored in a
prediction data storing unit; correcting a leveling target value on
the basis of the calculated deviation amount, the leveling target
value being a target value of power to be supplied from the
commercial power supply; and controlling the power supplying unit
so that the power supplying unit supplies power corresponding to
the corrected leveling target value from the commercial power
supply.
2. The power control method according to claim 1, further
comprising: predicting, for each of a plurality of candidate values
for the leveling target value, power to be supplied from the
commercial power supply during a predetermined period on the basis
of the each candidate value, data on a battery specification and
the power demand prediction data; and selecting one of the
candidate values as the leveling target value, a peak value of the
power predicted for the one of the candidate values being smallest
among the plurality of candidate values.
3. The power control method according to claim 2, wherein the
predicting includes: calculating, for each of the plurality of
candidate values, charge and discharge amounts of the battery on
the basis of the each candidate value, the data on the battery
specification and the power demand prediction data, predicting a
remaining battery level on the basis of the charge and discharge
amounts of the battery, and predicting, for each of a plurality of
candidate values, the power to be supplied from the commercial
power supply during the predetermined period on the basis of the
each candidate value, the power demand prediction data and data on
the predicted remaining battery level.
4. The power control method according to claim 1, further
comprising: predicting, for each of a plurality of candidate values
for the leveling target value, power to be supplied from the
commercial power supply during a predetermined period on the basis
of the each candidate value, data on a battery specification and
the power demand prediction data; calculating, for each of the
plurality of candidate values, a exhausted amount of carbon dioxide
during the predetermined period on the basis of data on the
predicted power and data on an amount of carbon dioxide exhausted
by generation of a unit amount of electricity; and selecting one of
the candidate values as the leveling target value, a determination
value being smallest among the plurality of candidate values, the
determination value being defined by a peak value of the power
predicted for the one of the candidate values and the exhausted
amount of carbon dioxide calculated for the one of the candidate
values.
5. The power control method according to claim 4, wherein the
predicting includes: calculating, for each of the plurality of
candidate values, charge and discharge amounts of the battery on
the basis of the each candidate value, the data on the battery
specification and the power demand prediction data predicting a
remaining battery level on the basis of the charge and discharge
amounts of the battery, and predicting, for each of a plurality of
candidate values, the power to be supplied from the commercial
power supply during the predetermined period on the basis of the
each candidate value, the power demand prediction data and data on
the predicted remaining battery level.
6. A power control method for a power supplying unit for supplying
power from a commercial power supply and a battery to a load,
comprising: calculating a deviation amount between an actual
remaining battery level and a predicted remaining battery level in
a predetermined unit period on the basis of battery level
transition data and data on the predicted remaining battery level,
the battery level transition data being stored in a battery
database; correcting a leveling target value on the basis of the
calculated deviation amount, the leveling target value being a
target value of power to be supplied from a commercial power
supply; and controlling the power supplying unit so that the power
supplying unit supplies power corresponding the corrected leveling
target value from the commercial power supply.
7. The power control method according to claim 6, further
comprising: predicting a remaining battery level on the basis of
the leveling target value, data on a battery specification and
power demand prediction data, the power demand prediction data
being stored in a prediction data storing unit.
8. A power control apparatus for a power supplying unit for
supplying power from a commercial power supply and a battery to a
load, comprising: a deviation calculation unit for calculating a
deviation amount between an actual power demand and a predicted
power demand in a predetermined unit period on the basis of power
demand transition data and power demand prediction data, the power
demand transition data being stored in a power database, the power
demand prediction data being stored in a prediction data storing
unit; a correction unit for correcting a leveling target value on
the basis of the calculated deviation amount, the leveling target
value being a target value of power to be supplied from the
commercial power supply; and a control unit for controlling the
power supplying unit so that the power supplying unit supplies
power corresponding to the corrected leveling target value from the
commercial power supply.
9. The power control apparatus according to claim 8, further
comprising: a power prediction unit for predicting, for each of a
plurality of candidate values for the leveling target value, power
to be supplied from the commercial power supply during a
predetermined period on the basis of the each candidate value, data
on a battery specification and the power demand prediction data;
and a selection unit for selecting one of the candidate values as
the leveling target value, a peak value of the power predicted for
the one of the candidate values being smallest among the plurality
of candidate values.
10. The power control apparatus according to claim 9, wherein the
power prediction unit includes: a charge and discharge calculation
unit for calculating, for each of the plurality of candidate
values, charge and discharge amounts of the battery on the basis of
the each candidate value, the data on the battery specification and
the power demand prediction data, and a battery level prediction
unit for predicting a remaining battery level on the basis of the
charge and discharge amounts of the battery, wherein the power
prediction unit predicts, for each of a plurality of candidate
values, the power to be supplied from the commercial power supply
during the predetermined period on the basis of the each candidate
value, the power demand prediction data and data on the predicted
remaining battery level.
11. The power control apparatus according to claim 8, further
comprising: a power prediction unit for predicting, for each of a
plurality of candidate values for the leveling target value, power
to be supplied from the commercial power supply during a
predetermined period on the basis of the each candidate value, data
on a battery specification and the power demand prediction data; an
exhaustion calculation unit for calculating, for each of the
plurality of candidate values, a exhausted amount of carbon dioxide
during the predetermined period on the basis of data on the
predicted power and data on an amount of carbon dioxide exhausted
by generation of a unit amount of electricity; and a selection unit
for selecting one of the candidate values as the leveling target
value, a determination value being smallest among the plurality of
candidate values, the determination value being defined by a peak
value of the power predicted for the one of the candidate values
and the exhausted amount of carbon dioxide calculated for the one
of the candidate values.
12. The power control apparatus according to claim 11, wherein the
power prediction unit includes: a charge and discharge calculation
unit for calculating, for each of the plurality of candidate
values, charge and discharge amounts of the battery on the basis of
the each candidate value, the data on the battery specification and
the power demand prediction data, and a battery level prediction
unit for predicting a remaining battery level on the basis of the
charge and discharge amounts of the battery, wherein the power
prediction unit predicts, for each of a plurality of candidate
values, the power to be supplied from the commercial power supply
during the predetermined period on the basis of the each candidate
value, the power demand prediction data and data on the predicted
remaining battery level.
13. A power control apparatus for a power supplying unit for
supplying power from a commercial power supply and a battery to a
load, comprising: a calculation unit for calculating a deviation
amount between an actual remaining battery level and a predicted
remaining battery level in a predetermined unit period on the basis
of battery level transition data and data on the predicted
remaining battery level, the battery level transition data being
stored in a battery database; a correction unit for correcting a
leveling target value on the basis of the calculated deviation
amount, the leveling target value being a target value of power to
be supplied from a commercial power supply; and a control unit for
controlling the power supplying unit so that the power supplying
unit supplies power corresponding the corrected leveling target
value from the commercial power supply.
14. The power control apparatus according to claim 13, further
comprising: a battery level prediction unit for predicting a
remaining battery level on the basis of the leveling target value,
data on a battery specification and power demand prediction data,
the power demand prediction data being stored in a prediction data
storing unit.
Description
CROSS-REFERENCE TO RELATED APPLICATION
This application is based upon and claims the benefit of priority
of the prior Japanese Patent Application No. 2010-095154, filed on
Apr. 16, 2010, the entire contents of which are incorporated herein
by reference.
FIELD
The embodiments disclosed herein relate to technologies which
control power to be supplied from a commercial power supply.
BACKGROUND
In recent years, many efforts have been made widely for suppressing
a peak of a power load for power load leveling.
Leveling a power load allows stable power supply from a power
supplier (such as electric power company) and can eliminate the
necessity for preparation of excessive electric power generation
equipment costs for a power load peak. Shifting daytime power loads
to the nighttime in which a lower proportion of power is generated
by thermal power generation can reduce the amount of carbon dioxide
exhausted when a unit amount of electricity is generated. On the
other hand, a power consumer (such as an office and a factory) can
advantageously reduce the power receiving equipment costs and/or
electricity charge.
By the way, in order to level power loads, a power consumer may
prepare a battery, and the battery is discharged in a time zone
with a large power load so that the peak value of power to be
supplied from a commercial power supply can be suppressed.
For example, when power supplied from a commercial system exceeds a
predetermined value, the excess amount of power may be discharged
from a power storage device so as to control the power to be
supplied from a commercial system so as not to be higher than a
desirable value (target demand value). However, according to this
technology, the discharging from a power storage device may not
address a power demand increase which is much higher than expected.
For that, power which is greatly higher than the desirable value is
supplied from the commercial system.
Reference may be made to Japanese Laid-open Patent Publication No.
2003-244840.
SUMMARY
According to an aspect of the embodiments, a power control method
for a power supplying unit for supplying power from a commercial
power supply and a battery to a load, includes calculating a
deviation amount between an actual power demand and a predicted
power demand in a predetermined unit period on the basis of power
demand transition data and power demand prediction data, the power
demand transition data being stored in a power database, the power
demand prediction data being stored in a prediction data storing
unit, correcting, by a computer, a leveling target value on the
basis of the calculated deviation amount, the leveling target value
being a target value of power to be supplied from the commercial
power supply, and controlling the power supplying unit so that the
power supplying unit supplies power corresponding to the corrected
leveling target value from the commercial power supply.
The object and advantages of the embodiment will be realized and
attained by means of the elements and combinations particularly
pointed out in the claims.
It is to be understood that both the foregoing general description
and the following detailed description are exemplary and
explanatory and are not restrictive of the invention, as
claimed.
BRIEF DESCRIPTION OF DRAWINGS
FIG. 1 is a configuration diagram of a system according to an
embodiment of the present technology;
FIG. 2 is a functional block diagram of a power management
server;
FIG. 3 illustrates an example of data stored in a battery DB;
FIG. 4 illustrates an example of data stored in a power demand
DB;
FIG. 5 illustrates an example of data stored in an analysis data
storage unit;
FIG. 6 illustrates an example of data stored in a prediction data
storing unit;
FIG. 7 illustrates a main processing flow according to this
embodiment;
FIGS. 8A to 8C are diagrams for explaining relationship between a
leveling desirable value and a remaining battery level;
FIGS. 9A to 9C are diagrams for explaining relationship between a
leveling desirable value and a remaining battery level;
FIGS. 10A to 10C are diagrams for explaining relationship between a
leveling desirable value and a remaining battery level;
FIG. 11 is diagrams for explaining relationship between a leveling
desirable value and the peak valve of supplied power;
FIG. 12 illustrates a processing flow of a first leveling
simulation;
FIG. 13 is a diagram for explaining the deviation between an actual
power demand and a predicted power demand;
FIG. 14 is a diagram for explaining how a leveling desirable value
is corrected;
FIG. 15 illustrates a processing flow of a first real time
correction processing;
FIG. 16 is a diagram for explaining the limitation on a time zone
for charging;
FIG. 17 illustrates a processing flow of a second leveling
simulation;
FIG. 18 illustrates the processing flow of the second leveling
simulation;
FIG. 19 is a diagram for explaining ideal transition of a remaining
battery level;
FIG. 20 is a diagram for explaining the deviation between an actual
remaining battery level and a predicted remaining battery
level;
FIG. 21 illustrates a processing flow of second real time
correction processing; and
FIG. 22 is a function block diagram of a computer.
DESCRIPTION OF EMBODIMENTS
First Embodiment
FIG. 1 is a configuration diagram of a system according to an
embodiment. For example, to a network 1 which is an intra LAN
(Local Area Network), a power management server 3, a power
supplying unit 5, a measuring apparatus 7, and a management
terminal 13 are connected. Furthermore, for example, a commercial
power supply 9 which is a power receiving apparatus supplies power
to the power supplying unit 5. The power supplying unit 5 may be an
Uninterruptible Power Supply (UPS), for example, and may supply
power to a load 11 which is an apparatus that consumes power, such
as a personal computer, a printer, and a lighting, for example.
The power supplying unit 5 includes a communication unit 501, a
power operation unit 503, a battery 505, a charging control unit
507, a discharging control unit 509, and a power demand monitoring
unit 511.
The communication unit 501 performs processing including
transmitting data on a remaining battery level to the power
management server 3 and receiving a control request including data
on a desirable value (hereinafter called a leveling desirable
value) of maximum power to be supplied from the commercial power
supply 9 from the power management server 3. The power operation
unit 503 calculates charge power and discharge power and performs
processing including instructing the charging control unit 507 to
charge the calculated charge power and instructing the discharging
control unit 509 to discharge the calculated discharge power. The
charging control unit 507 performs processing including charging
the charge power instructed by the power operation unit 503 to the
battery 505 and measuring a remaining battery level and notifying
it to the power operation unit 503. The discharging control unit
509 performs processing including discharging the discharge power
instructed from the power operation unit 503 to the load 11. The
power demand monitoring unit 511 performs processing including
measuring the power demand of the load 11 and notifying it to the
power operation unit 503.
The measuring apparatus 7 includes a communication unit 701 and a
power demand measuring unit 703.
The communication unit 701 transmits data on a power demand to the
power management server 3. The power demand measuring unit 703
measures the power demand of the load 11 and notifies it to the
communication unit 701.
FIG. 2 is a functional block diagram of the power management server
3. The power management server 3 includes an optimization control
unit 301, a real-time correction unit 303, a long-term prediction
unit 305, a short-term tendency data generating unit 307, an
analysis data storage unit 309, an analysis unit 311, a power
demand DB 313, a battery DB 315, a communication unit 317, and a
control data storage unit 319.
The optimization control unit 301 includes a leveling simulator
3011, and an optimum value searching unit 3013.
The real-time correction unit 303 includes an amount-of-correction
calculating unit 3031, and a leveling control unit 3033.
A long-term prediction unit 305 includes a prediction data
generating unit 3051, a prediction data storing unit 3053, and a
prediction data searching unit 3055.
The communication unit 317 receives data on a remaining battery
level from the power supplying unit 5 and stores it in the battery
DB 315. The communication unit 317 receives data on a measured
power demand from the measuring apparatus 7 and stores it in the
power demand DB 313. The analysis unit 311 performs processing on
data stored in the power demand DB 313, including calculating a
mean value in a unit period of time such as 30 minutes and stores
the result in the analysis data storage unit 309. The prediction
data generating unit 3051 uses data stored in the analysis data
storage unit 309 to generate prediction data on a power demand for
each characteristic such as the day of the week and an event of a
day when a power demand is measured, for example, and stores it in
the prediction data storing unit 3053. The prediction data
searching unit 3055 extracts the prediction data corresponding to
the characteristic of the day when processing of this embodiment is
performed (hereinafter, called a control target day) from the
prediction data storing unit 3053 and notifies it to the optimum
value searching unit 3013. The short-term tendency data generating
unit 307 performs processing of generating data on a short-term
tendency of a power demand and remaining battery level and notifies
them to the amount-of-correction calculating unit 3031.
The communication unit 317 receives data on a characteristic of a
control target day and data on a battery specification from the
management terminal 13 and stores it to control data storage unit
319. The optimum value searching unit 3013 performs processing of
searching a leveling desirable value on the basis of data stored in
the control data storage unit 319 and data notified from the
prediction data searching unit 3055. The leveling simulator 3011
performs a leveling simulation, which will be described later. The
amount-of-correction calculating unit 3031 performs real time
correction processing, which will be described later, on the basis
of the data notified from the optimum value searching unit 3013 and
short-term tendency data generating unit 307 and notifies the
processing result to the leveling control unit 3033. The leveling
control unit 3033 generates a control request including data on a
corrected leveling desirable value and instructs the communication
unit 317 to transmit the control request. The communication unit
317 transmits the control request to the power supplying unit
5.
FIG. 3 illustrates an example of data stored in the battery DB 315.
The example in FIG. 3 includes a date and time column and an amount
of electric energy column.
FIG. 4 illustrates an example of data stored in the power demand DB
313. The example in FIG. 4 includes a date and time column and a
power column.
FIG. 5 illustrates an example of data stored in the analysis data
storage unit 309. The example in FIG. 5 includes a date and time
column and a power column. In the example in FIG. 5, data on a
power demand every 30 minutes are stored.
FIG. 6 illustrates an example of data stored in the prediction data
storing unit 3053. The example in FIG. 6 includes a characteristic
column, a date and time column, and a power column. The prediction
data may be generated by, for example, averaging the data of power
demands on the days having a common characteristic. While data on
the day of the week is stored as the characteristic data in the
example in FIG. 6, the data may be data on a month or an event or
the combination of them, for example. The characteristic data may
be extracted from an intra-company scheduler, for example.
Next, with reference to FIG. 7 to FIG. 15, the details of the
processing by the system illustrated in FIG. 1 will be described.
First of all, the management terminal 13 receives from a manager
the input of data on a characteristic on a control target day (such
as the day of the week, a month, and a scheduled event) and data on
a battery specification (such as a capacity, initial remaining
level, and a maximum value of charge and discharge power of a
battery). Then, the management terminal 13 transmits a desirable
value setting request including the data on a characteristic on the
control target day and data on a battery specification to the power
management server 3. The communication unit 317 in the power
management server 3 receives the desirable value setting request
from the management terminal 13 and stores it in the control data
storage unit 319 (FIG. 7, step S1).
The optimum value searching unit 3013 requests the prediction data
searching unit 3055 to extract prediction data on the power demand
corresponding to the control target day. The prediction data
searching unit 3055 extracts the prediction data on the power
demand corresponding to the control target day from the prediction
data storing unit 3053 and outputs it to the optimum value
searching unit 3013 (step S3).
The optimum value searching unit 3013 specifies one candidate value
e for the leveling desirable value (step S5). In order to specify a
candidate value e for the leveling desirable value, a metaheuristic
method such as PSO (Particle Swarm Optimization) and GA (Genetic
Algorithm) may be used, for example. The methods will not be
described in detail since they are not a main part of this
embodiment. In step S5, the optimum value searching unit 3013
outputs candidate value e, data stored in the control data storage
unit 319 and prediction data on a power demand corresponding to the
control target day to the leveling simulator 3011.
Next, the leveling simulator 3011 performs a leveling simulation
(step S7). The leveling simulation will be described with reference
to FIG. 8A to FIG. 12. The leveling simulator 3011 includes a power
prediction unit for predicting, for each of a plurality of
candidate values for a leveling target value, power to be supplied
from a commercial power supply and a selection unit for selecting
one of the candidate values as the leveling target value, as
explained below. Further, the leveling simulator 3011 includes a
charge and discharge calculation unit for calculating, for each of
the plurality of candidate values, charge and discharge amounts of
the battery, and a battery level prediction unit for predicting a
remaining battery level, as explained below.
The leveling simulation according to this embodiment calculates the
peak value of the power supplied from a commercial power supply for
each candidate value. First of all, with reference to FIG. 8A to
FIG. 10, there will be described the relationship among the
magnitude of a candidate value e, the prediction value for the
remaining battery level and the prediction value of power supplied
from a commercial power supply. In FIG. 8A to FIG. 10C, the
vertical axis on the left side indicates the power [kW], and the
vertical axis on the right side and horizontal axis indicate the
remaining battery level [%] and the time, respectively.
FIGS. 8A to 8C illustrate a case where the candidate value e is set
to 14 kW. In the example in FIGS. 8A to 8C, the power demand
increases at a time T1. When the power demand exceeds the leveling
desirable value (14 kW) (FIG. 8A), the battery is started to
discharge. Then, the remaining battery level decreases (FIG. 8B).
After that, until a time T2, the remaining battery level keeps
decreasing (FIG. 8B). When the power demand falls to below the
leveling desirable value at the time T2 (FIG. 8A), the battery is
started to charge. Then, the remaining battery level increases
(FIG. 8B). After that, until a time T3, the remaining battery level
keeps increasing (FIG. 8B). When the power demand increases and
exceeds the leveling desirable value at the time T3 (FIG. 8A), the
battery is started to discharge. Then, the remaining battery level
decreases again (FIG. 8B). When the remaining battery level reaches
0% at a time T4 (FIG. 8B), the power supplied from the commercial
power supply rapidly increases (the part enclosed by the dashed
line in FIG. 8C). This is because the power demand is only met by
the supplied power from the commercial power supply. At a time T5
after that, the power demand falls to below the leveling desirable
value (FIG. 8A), the power supplied from the commercial power
supply returns to the leveling desirable value (FIG. 8C). Then, the
battery is started to charge (FIG. 8B).
On the other hand, FIGS. 9A to 9C illustrate a case where the
candidate value e is set to 15 kW. In the example in FIGS. 9A to
9C, the remaining battery level has a similar transition to that in
FIGS. 8A to 8C, but the remaining battery level does not reach 0%
(FIG. 9B). This is because a less amount of power is required to
discharge from the battery since the candidate value e is set to a
higher value than that in the example in FIGS. 8A to 8C. This can
prevent the rapid increase of power to be supplied from a
commercial power supply as in the example in FIGS. 8A to 8C (FIG.
9C).
FIGS. 10A to 10C illustrate a case where the candidate value e is
set to 16 kW. Also in the example in FIGS. 10A to 10C, like the
example in FIGS. 9A to 9C, because the candidate value e is set to
a higher value than that in the example in FIGS. 8A to 8C, the
power supplied from a commercial power supply does not rapidly
increase (FIG. 10C). However, in the example in FIGS. 10A to 10C,
the battery still has a remaining battery level of about 25% even
at the times T2 and T5 with the shortest remaining battery level
(FIG. 10B), and the battery may not be used as effectively as in
the example in FIGS. 9A to 9C.
FIG. 11 illustrates a relationship between a peak value of power
supplied from a commercial power supply and a candidate value. In
FIG. 11, the vertical axis indicates peak value [kW] of the power
supplied from a commercial power supply, and the horizontal axis
indicates candidate value [kW]. In the example in FIG. 11, when the
candidate value is equal to or lower than 14 kW, the remaining
battery level reaches 0. Thus, the power supplied from a commercial
power supply increases significantly. On the other hand, when the
leveling desirable value is equal to or higher than 15 kW, the
remaining battery level does not reach 0%. The peak value of the
power supplied from a commercial power supply then is equal to the
leveling desirable value. In this case, the optimum value as the
leveling desirable value is equal to 15 kW. In other words,
according to this embodiment, a leveling simulation is performed
for each candidate value, and the peak value of the power supplied
from a commercial power supply is calculated. Then, the candidate
value with a minimum peak value is specified as the leveling
desirable value.
Next, with reference to FIG. 12, details of processing in the
leveling simulation will be described. First of all, the leveling
simulator 3011 sets Ppeak=0 and T=Tstart as the initial values
(step S21). Ppeak is the peak value of the power supplied from a
commercial power supply. Tstart is the beginning time of the period
for calculation.
The leveling simulator 3011 then determines whether T has overrun
Tend or not (step S23). Tend is the end time of the period for
calculation. If it is determined that T has overrun Tend (Yes in
step S23), the end of the calculation can be determined. Thus, the
leveling simulator 3011 notifies the calculation result (the peak
value of the power supplied from a commercial power supply) to the
optimum value searching unit 3013. Then, the processing returns to
the beginning.
On the other hand, if it is determined that T has not exceeded Tend
(No in step S23), the leveling simulator 3011 uses a candidate
value e and predicted power demand value D to calculate a
prediction value of the charge/discharge amount for the battery and
stores it in a storage such as a main memory (step S25). For
example, the relationship between D and e may be used for the
calculation. If it is D<e, charging may be performed. If it is
D>e, discharging may be performed. If the data on the battery
specification received in step S1 includes data on a maximum charge
power and a maximum discharge power, the charge/discharge amount
not exceeding those values are calculated.
Next, the leveling simulator 3011 uses a prediction value of the
battery charge/discharge amount to calculate the prediction value
of the remaining battery level B after charging/discharging and
stores it in a storage such as a main memory (step S27). For
example, B=Bpre-(the prediction value of the charge/discharge
amount) may be used for the calculation. Bpre is the battery level
before the predicted charging/discharging is performed. If the data
on the remaining battery level received in step S1 includes data on
the capacity or initial remaining level of the battery, the value
may be used.
The leveling simulator 3011 calculates the prediction value P of
the supplied power from the prediction value B of the remaining
battery level after charging/discharging and stores it in a storage
such as a main memory (step S29). For example, if it is B=0, the
power demand is met only with the supplied power from a commercial
power supply. Thus, the prediction value P of the supplied power is
equal to the prediction value D of the power demand. On the other
hand, if it is B.noteq.0, the prediction value P of the supplied
power is equal to the prediction value D of the power demand when
the prediction value D of the power demand has not reached the
candidate value e yet. The prediction value P of the supplied power
is equal to the candidate value e if the prediction value D of the
power demand has already reached the candidate value e.
The leveling simulator 3011 then determines whether it is
Ppeak<P or not (step S31). If it is not Ppeak<P (No in step
S31), the processing moves to step S35.
On the other hand, if it is Ppeak<P (Yes in step S31), the
leveling simulator 3011 sets Ppeak=P (step S33). The leveling
simulator 3011 then advances T by a unit time (step S35), and the
processing moves to step S23.
Performing the processing as described above allows the
specification of the leveling desirable value from the viewpoint of
minimization of the peak value of the power supplied from a
commercial power supply.
Referring back to FIG. 7, the optimum value searching unit 3013
determines whether the leveling simulation has performed a
predetermined number of times or not (step S9). If not (No in step
S9), the processing returns to step S5 to process the next
candidate value. If so on the other hand (Yes in step S9), the
optimum value searching unit 3013 specifies the candidate value
which provides a minimum peak value of the power supplied from a
commercial power supply as a leveling desirable value E (step S11).
In step S11, the optimum value searching unit 3013 notifies the
power demand prediction data and the specified leveling desirable
value E to the amount-of-correction calculating unit 3031.
Next, the amount-of-correction calculating unit 3031 performs real
time correction processing (step S13). The real time correction
processing will be described with reference to FIG. 13 to FIG. 15.
The amount-of-correction calculating unit 3031 includes a deviation
calculation unit for calculating a deviation amount between an
actual power demand and a predicted power demand and a correction
unit for correcting a leveling target value, as explained
below.
FIG. 13 illustrates the transition of a measured power demand and a
predicted power demand. The vertical axis of FIG. 13 indicates
power [kW], and the horizontal axis indicates time. It is assumed
that the real time correction processing is performed at a time T2.
In the example in FIG. 13, the measured power demand shifts without
largely deviating from the prediction until the time T1. From the
time T1 to the time T2, the deviation gradually increases, and the
deviation is significantly large at the time T2. Keeping this state
may significantly raise the peak value of the power supplied from a
commercial power supply since the discharged power from the battery
is larger than predicted and the remaining battery level may reach
0%.
Accordingly, the real time correction processing according to this
embodiment corrects the leveling desirable value. FIG. 14
illustrates the case where the leveling desirable value is set to a
higher value. The vertical axis indicates power [kW], and the
horizontal axis indicates time. In the example in FIG. 14, the
leveling desirable value is corrected at the time T2. Thus, the
discharged power from the battery decreases. According to this
embodiment, the real time correction processing is performed every
lapse of a unit period of time (such as 30 minutes) so that the
peak value of the power supplied from a commercial power supply can
be prevented from being significantly high, as will be described
below.
Next, with reference to FIG. 15, details of the real time
correction processing will be described. First of all, the
amount-of-correction calculating unit 3031 calculates the mean
value of the power demand prediction values for the last unit
period on the basis of power demand prediction data and stores it
in a storage such as a main memory (FIG. 15, step S41). For
example, if the power demand prediction data are for every 30
minutes as illustrated in FIG. 6 and the last unit period is the 30
minutes from 11:00 to 11:30, the mean value between the power
demand prediction value at 11:00 and the power demand prediction
value at 11:30 is calculated.
Next, the amount-of-correction calculating unit 3031 instructs the
short-term tendency data generating unit 307 to generate data on a
short-term tendency of actual power demands. The short-term
tendency data generating unit 307 extracts data on power demands in
the last unit period from the power demand DB 313, calculates the
mean value of the power demands in the last unit period, and
notifies it to the amount-of-correction calculating unit 3031 (step
S43).
The amount-of-correction calculating unit 3031 subtracts the mean
value of the predicted power demands calculated in step S41 from
the mean value of the actual power demands calculated in step S43
to calculate a Pdiff and stores it in a storage such as a main
memory (step S45).
The amount-of-correction calculating unit 3031 then determines
whether it is Pdiff>0 or not (step S47). If it is not Pdiff>0
(No in step S47), the processing moves to step S51. In step S47,
whether Pdiff is higher than 0 or not is determined, but whether
Pdiff is higher than a predetermined threshold value or not may be
determined.
On the other hand, if it is determined that it is Pdiff>0 (Yes
in step S47), the amount-of-correction calculating unit 3031
calculates a leveling desirable value E=Epres+.alpha..times.Pdiff
and stores it in a storage such as a main memory (step S49). Epres
is the leveling desirable value before correction. .alpha. is the
amount of correction for Pdiff. For example, if .alpha. is equal to
0, the leveling desirable value E is not corrected. If .alpha.=1, E
is corrected to compensate the entire power shortage.
Next, the amount-of-correction calculating unit 3031 notifies the
leveling desirable value E after the correction to the leveling
control unit 3033. The leveling control unit 3033 generates a
control request including data on the leveling desirable value E
after the correction and transmits it to the power supplying unit 5
(step S51).
The processing to be performed in the power supplying unit 5 will
be described below. The communication unit 501 in the power
supplying unit 5 receives the control request from the power
management server 3 and stores it in a storage such as a main
memory. The communication unit 501 notifies the data on the
leveling desirable value E included in the control request to the
power operation unit 503. The power operation unit 503 compares the
actual power demand notified from the power demand monitoring unit
511 and the leveling desirable value E and determines whether
charging or discharging is performed. Here, since the actual power
demand is higher than the leveling desirable value E, the battery
505 is discharged. The power operation unit 503 instructs the
discharging control unit 509 to control the discharging from the
battery 505 and power supplied from the commercial power supply 9.
The discharging control unit 509 controls the commercial power
supply 9 so as to supply power that is equivalent to the leveling
desirable value E and controls the battery 505 so as to discharge
the power shortage.
Referring back to FIG. 15, the amount-of-correction calculating
unit 3031 waits until a unit period passes (step S53). After a
lapse of the unit period, whether the period in which the real time
correction is to be performed (such as one day) has passed or not
is determined (step S55). If not (No in step S55), the processing
returns to step S41 to perform the process in the next unit period.
If so on the other hand (Yes in step S55), the processing returns
to the beginning and ends.
Performing the processing as described above can prevent
significant increase of the peak value of the power supplied from a
commercial power supply even when the actual power demand is
greatly deviated from the predicted power demand.
Second Embodiment
Next, a second embodiment will be described. According to the
aforementioned first embodiment, the leveling desirable value is
specified such that the peak value of the power supplied from a
commercial power supply can be a minimum. According to the second
embodiment on the other hand, the leveling desirable value is
specified such that not only the peak value of the power supplied
from a commercial power supply but also the amount of carbon
dioxide exhausted by electric power generation can be reduced.
Since the configuration diagram of the system according to this
embodiment and the function block diagram of the power management
server 3 are the same as those described according to the first
embodiment, the description will be omitted.
Next, with reference to FIG. 16 to FIG. 18, a leveling simulation
(step S7) according to this embodiment will be described. First of
all, with reference to FIG. 16, the concept of a leveling
simulation according to this embodiment will be described. In FIG.
16, the vertical axis indicates power [kW], and the horizontal axis
indicates time. In the example in FIG. 16, the nighttime (such as
23:00 to 7:00 in the next morning) from a time T0 to a time T1 and
from a time T4 to a time T5 is handled as a chargeable time zone.
In the example in FIG. 16, charging is performed from the time T0
to the time T1 and from the time T4 to the time T5. Charging and
discharging are not performed from the time T1 to the time T2 and
from the time T3 to the time T4. Discharging is performed from the
time T2 to the time T3.
In this way, generating the relatively larger proportion of the
amount of electricity during a time zone such as the nighttime with
a less amount of carbon dioxide exhausted by generation of a unit
amount of electricity can reduce the exhausted amount of carbon
dioxide as a whole. According to Kajiyama et al., "Raihusaikuru
Kara Mita Chikudenchi No Denryokuhu Kaheijyunka Niyoru
Enerugi/Kankyou Kaizen Kouka (Energy and environmental analysis of
batteries for electric load leveling using LCA method)", Journal of
Life Cycle Assessment, Vol. 2 No. 4, October 2006), the amount of
carbon dioxide exhausted when energy of 1 kWh is generated is 514 g
during the daytime (from 8:00 to 23:00) and 391 g during the
nighttime (from 23:00 to the next 8:00). This is because, during
the nighttime, the proportion of energy generated by thermal power
generation is lower, and the proportion of the energy generated by
nuclear electric power generation is higher, for example.
Next, with reference to FIG. 17 and FIG. 18, details of a leveling
simulation according to this embodiment will be described. The
leveling simulator 3011 includes an exhaustion calculation unit for
calculating, for each of a plurality of candidate values for a
leveling target value, an exhausted amount of carbon dioxide in
addition to a power prediction unit and a selection unit disclosed
in the aforementioned first embodiment.
First of all, the leveling simulator 3011 sets Cemit=0, Ppeak=0 and
T=Tstart as the initial values (step S61). Cemit is the amount of
carbon dioxide exhausted by electric power generation. Ppeak is the
peak value of the power supplied from a commercial power supply.
Tstart is the beginning time of the period for calculation.
The leveling simulator 3011 determines whether T has overrun Tend
or not (step S63). Tend is the end time of the period for
calculation. If it is determined that T has overrun Tend (Yes in
step S63), the leveling simulator 3011 calculates an objective
function f=.beta.Ppeak+.gamma.Cemit and stores it in a storage such
as a main memory (step S65). .beta. and .gamma. are determined
depending on which of the minimization of the peak value of the
power supplied from a commercial power supply and the minimization
of the exhaust amount of carbon dioxide has priority. If it is set
as .beta.=1 and .gamma.=0, a candidate value which provides a
minimum peak value of the power supplied from a commercial power
supply is specified as a leveling desirable value, like the first
embodiment. In step S65, the leveling simulator 3011 notifies the
calculation result (objective function f) to the optimum value
searching unit 3013 and returns to the beginning. In step S11,
instead of the peak value Ppeak of the power supplied from a
commercial power supply, a candidate value e which provides a
minimum objective function f is specified as the leveling desirable
value.
On the other hand, if it is determined that T has not overrun Tend
(No in step S63), the leveling simulator 3011 determines whether it
is candidate value e<power demand prediction value D or not
(step S67).
If it is determined that candidate value e<power demand
prediction value D (Yes in step S67), the leveling simulator 3011
calculates Pdisch=D-e and stores it in a storage such as a main
memory (step S69). Pdisch is the amount of discharging from a
battery. The leveling simulator 3011 sets Pch=0 and stores it in a
storage such as a main memory (step S71). Pch is the amount of
charging to the battery.
On the other hand, if it is not candidate value e<power demand
prediction value D (No in step S67), the leveling simulator 3011
sets Pdisch=0 and stores it in a storage such as a main memory
(step S73). The leveling simulator 3011 determines whether T is
included in a chargeable time zone or not (step S75).
If it is determined that T is not included in the chargeable time
zone (No in step S75), the leveling simulator 3011 sets Pch=0 and
stores it in a storage such as a main memory (step S77).
On the other hand, if it is determined that T is included in the
chargeable time zone (Yes in step S75), the leveling simulator 3011
sets Pch=e-D and stores it in a storage such as a main memory (step
S79). The processing then moves to step 81 in FIG. 18 through a
terminal A.
If the data on a battery specification received in step S1 includes
data on a maximum charge power and a maximum discharge power, Pch
and Pdisch are calculated such that they are under the maximum
values.
With reference to FIG. 18, the processing after the terminal A will
be described. First of all, the leveling simulator 3011 calculates
a prediction value B of the remaining battery level after
charging/discharging from Pch and Pdisch and stores it in a storage
such as a main memory (step S81). For example, B=Bpre+Pch-Pdisch
may be used for the calculation. Bpre is the battery level before
the predicted charging/discharging is performed. If the data on the
remaining battery level received in step S1 includes data on the
capacity or initial remaining level of the battery, the value may
be used for calculating B.
The leveling simulator 3011 calculates the prediction value P of
the supplied power from the prediction value B of the remaining
battery level after charging/discharging and stores it in a storage
such as a main memory (step S83). For example, if it is B=0, the
power demand is met only with the supplied power from a commercial
power supply. Thus, the prediction value P of the supplied power is
equal to the prediction value D of the power demand. On the other
hand, if it is B.noteq.0, the prediction value P of the supplied
power is equal to the prediction value D of the power demand when
the prediction value D of the power demand has not reached the
candidate value e yet. The prediction value P of the supplied power
is equal to the candidate value e if the prediction value D of the
power demand has already reached the candidate value e.
The leveling simulator 3011 then determines whether it is
Ppeak<P or not (step S85). If it is not Ppeak<P (No in step
S85), the processing moves to step S89.
On the other hand, if it is Ppeak<P (Yes in step S85), the
leveling simulator 3011 sets Ppeak=P and stores it in a storage
such as a main memory (step S87). The leveling simulator 3011 sets
Cemit=Cemit_pres+.delta.P and stores it in a storage such as a main
memory (step S89). Cemit_pres is the present amount of carbon
dioxide exhausted by electric power generation. .delta. is the
amount of carbon dioxide (g/kWh) exhausted when a unit amount of
electricity is generated, and different values may be set in
accordance with the time zones.
Next, the leveling simulator 3011 advances T by a unit time (step
S91). The processing then returns to step S63 in FIG. 17 through a
terminal B.
Performing the processing as described above allows the
specification of the leveling desirable value from the viewpoint of
minimization of the peak value of the power supplied from a
commercial power supply and minimization of the exhausted amount of
carbon dioxide.
Third Embodiment
Next, a third embodiment will be described. According to the
aforementioned first embodiment, the deviation between an actual
power demand and a predicted power demand is monitored, and the
leveling desirable value is corrected in accordance with the degree
of deviation. On the other hand, according to this embodiment, the
deviation between an actual remaining battery level and a predicted
remaining battery level, and the leveling desirable value is
corrected in accordance with the degree of deviation.
Since the configuration diagram of the system according to this
embodiment and the function block diagram of the power management
server 3 are the same as those described according to the first
embodiment, the description will be omitted.
Next, with reference to FIG. 19 to FIG. 21, real time correction
processing according to this embodiment will be described. The
amount-of-correction calculating unit 3031 includes a calculation
unit for calculating a deviation amount between an actual remaining
battery level and a predicted remaining battery level and a
correction unit for correcting a leveling target value, as
explained below. Further, the amount-of-correction calculating unit
3031 includes a battery level prediction unit for predicting a
remaining battery level, as explained below.
First of all, with reference to FIG. 19 and FIG. 20, the concept of
real time correction according to this embodiment will be
described. In FIG. 19 and FIG. 20, the vertical axis on the left
side indicates power [kW], and the vertical axis on the right side
and the horizontal axis indicate remaining battery level [%] and
time, respectively.
In the example in FIG. 19, since the power demand is lower than a
leveling desirable value until a time T1, the remaining battery
level does not change. After that, when the power demand exceeds
the leveling desirable value at the time T1, the battery is started
to discharge. Thus, the remaining battery level starts decreasing.
When the power demand falls to below the leveling desirable value
at a time T2, the battery is started to charge. Thus, the remaining
battery level starts increasing. In this way, if the power demand
has a transition as predicted, the remaining battery level does not
reach 0.
However, like the example in FIG. 20, the speed of decrease of the
remaining battery level may sometimes be higher than predicted. In
the example in FIG. 20, since the speed of decrease of the
remaining battery level is higher than predicted, the remaining
battery level reaches 0% at a time T3 if the remaining battery
level keeps decreasing at the speed. Accordingly, in the example in
FIG. 20, the leveling desirable value is set to a higher value from
the time T1 to the time T2. Thus, the speed of decrease of the
remaining battery level can be reduced, which can prevent the
remaining battery level from reaching 0%. As will be described
below, according to this embodiment, the degree of deviation of the
remaining battery level is monitored every lapse of a unit period
(such as 30 minutes), and the leveling desirable value is corrected
as required. Thus, the peak value of the power supplied from a
commercial power supply can be prevented from being significantly
higher.
Next, with reference to FIG. 21, details of real time correction
processing (step S13) according to this embodiment will be
described. First of all, the amount-of-correction calculating unit
3031 calculates the prediction value of the remaining battery level
and stores it in a storage such as a main memory (FIG. 21, step
S101). The processing in step S101 uses data on a leveling
desirable value E, a power demand prediction value D and a battery
specification to perform the same processing as in step S25 and
S27. In step S101, the prediction value of the remaining battery
level for a period (such as one day) for performing the real time
correction is calculated.
Next, the amount-of-correction calculating unit 3031 instructs the
short-term tendency data generating unit 307 to notify data on the
actual remaining battery level. The short-term tendency data
generating unit 307 reads the data on the remaining battery level
at the point in time when the real time correction processing is
performed from the battery DB 315 and notifies it to the
amount-of-correction calculating unit 3031 (step S103).
The amount-of-correction calculating unit 3031 subtracts the
predicted remaining battery level calculated in step S101 from the
actual remaining battery level notified in step S103 to calculate
an Rdiff and stores it in a storage such as a main memory (step
S105).
The amount-of-correction calculating unit 3031 then determines
whether it is Rdiff>0 or not (step S107). If it is not
Rdiff>0 (No in step S107), the processing moves to step S113. In
step S107, while whether Rdiff is higher than 0 or not is
determined, whether Rdiff is higher than a predetermined threshold
value or not may be determined.
On the other hand, if it is determined Rdiff>0 (Yes in step
S107), the amount-of-correction calculating unit 3031 calculates
the amount of correction .epsilon. for supplying the amount of
electricity that is equivalent to Rdiff from a commercial power
supply in a unit period and stores it in a storage such as a main
memory (step S109). For example, .epsilon.=Rdiff/(unit period) may
be used. The amount-of-correction calculating unit 3031 calculates
a leveling desirable value E=Epres+.alpha..epsilon. and stores it
in a storage such as a main memory (step S111). For example, if
.alpha. is equal to 0, the leveling desirable value E is not
corrected. If .alpha.=1, E is corrected to compensate the entire
remaining battery power shortage.
Next, the amount-of-correction calculating unit 3031 notifies the
leveling desirable value E after the correction to the leveling
control unit 3033. The leveling control unit 3033 generates a
control request including data on the leveling desirable value E
after the correction and transmits it to the power supplying unit 5
(step S113). The processing to be performed in the power supplying
unit 5 after the processing in step S113 is as described according
to the first embodiment.
The amount-of-correction calculating unit 3031 waits until a unit
period passes (step S115). After a lapse of the unit period,
whether the period in which the real time correction is to be
performed has passed or not is determined (step S117). If not (No
in step S117), the processing returns to step S103 to perform the
process for the next unit period. If so on the other hand (Yes in
step S103), the processing returns to the beginning and ends.
Performing the processing as described above can prevent running
out of the battery and can suppress the peak value of the power
supplied from a commercial power supply even when the remaining
battery level decreases faster than expected.
Having described the embodiments of the present technology, the
present technology is not limited thereto. For example, the
function block diagrams of the power management server 3, power
supplying unit 5 and measuring apparatus 7 do not typically
correspond to the actual program modules.
The configurations of the tables are given for illustration
purposes only, and the configurations are not typically required.
The order of the steps may be changed in the processing flows if
the processing results are the same. The steps may be performed in
parallel.
The client-server type system illustrated in FIG. 1 is given for
illustration purposes only, and it may be a standalone type
system.
In the real time correction processing, if the actual power demand
or remaining battery level exceeds the prediction, the leveling
desirable value is corrected. However, the leveling desirable value
may be corrected to a lower value if it falls to below the
prediction.
In the example described above, the power management server 3
transmits a control request for the leveling desirable value to the
power supplying unit 5 and controls the leveling desirable value
through the power supplying unit 5. However, the power management
server 3 may transmit a control request for the leveling desirable
value to the commercial power supply 9 and directly control the
leveling desirable value. The power supplying unit 5 calculates the
amount to charge or discharge the battery 505 to control the
charging/discharging to/from the battery 505 on the basis of the
leveling desirable value notified from the power management server
3 and a measured power demand.
In the power management server 3 and management terminal 13, as
illustrated in FIG. 22, a memory 2501 (storing unit), a CPU 2503
(processing unit), a hard disk drive (HDD) 2505, a display control
unit 2507 connected to a display apparatus 2509, a driver 2513 for
a removable disk 2511, an input device 2515, and a communication
control unit 2517 for connecting to a network are connected via a
bus 2519. Application programs including an OS and a Web browser
are stored in the HDD 2505 and are read from the HDD 2505 to the
memory 2501 to execute by the CPU 2503. When the necessity rises,
the CPU 2503 controls the display control unit 2507, communication
control unit 2517, and driver 2513 so as to perform necessary
operations. Data being processed are stored in the memory 2501 and
may be stored in the HDD 2505 if necessary. This kind of computer
may implement the functions as described above with organic
collaboration in hardware such as between the CPU 2503 and the
memory 2501, an OS and a necessary application program.
A program causing a computer to perform processings according to
the methods disclosed in the above embodiments may be generated.
The program may be stored in a computer-readable storage medium or
storage device such as a flexible disk, a CD-ROM, a magneto-optical
disk, a semiconductor memory, and a hard disk, for example. The
intermediate processing results may be temporarily stored in a
storage such as a main memory.
All examples and conditional language recited herein are intended
for pedagogical purposes to aid the reader in understanding the
invention and the concepts contributed by the inventor to
furthering the art, and are to be construed as being without
limitation to such specifically recited examples and conditions,
nor does the organization of such examples in the specification
relate to a showing of the superiority and inferiority of the
invention. Although the embodiments of the present invention have
been described in detail, it should be understood that the various
changes, substitutions, and alterations could be made hereto
without departing from the spirit and scope of the invention.
* * * * *